To do

1 Intro

1.1 Context

One of the goals of sepages is to analyse the link between exposure to endocrine disruptors during pregnancy and the infant’s neurological development. One of the experiments to quantify neurologic development was to perform eye tracking experiments at Grenoble’s LPNC BabyLab. Sepages infants were subject to several tasks and were seen up to 3 times: at 5 months, 12 months, 24 months.

Here are the descriptive stats on the babylab dataset DataFile_030220_anonym_id.csv.

First we present the different tasks and scores. Then we briefly describe the population. Finally we decide on a subselection of scores for final analysis.

1.2 Eye tracking

Eye movement is measured by X-Y coordinates continuously. Eye movement consists of a sequence of saccades (movement) and fixations (non movements). Using the eye tracker several tasks are performed for which various scores were computed. Four tasks were performed for this study:

  • scene perception
  • face perception and recognition
  • saccades to target
  • smooth pursuit

1.2.1 Task 1: Scene perception

An image is shown to the baby for five seconds each. The experiment is repeated six times.

We are interested in looking at what part of the image the infant looks at.

The scores available for this task are

  1. The number of saccades during the task (n_sacc_1)
  2. The values of a and b in the equation v = b*d^a (param1_1 & param2_1)
  3. The mean number of fixations over the six images (n_fix_mean_1)
  4. The mean total time spent looking at the image (look_t_mean_1)
  5. The mean duration of one fixation (dur_fix_mean_1)
  6. A score to compute if the child looks at the same place of the image or not as the other children (map_mean_1)

1.2.2 Task 2: Face perception and recognition

Two pictures of the same human face are simultaneously shown to the baby for 5 seconds. Then, one picture is replaced by a new one (the faces have different levels of attractiveness) and the two different pictures are shown to the baby for 5 seconds. The experiment is repeated four times.

We are interested in measuring the reaction to novelty: the baby should preferentially look at the new face.

But problem here: the duration of exposure to the different pictures is too long. WHY???

The scores available for this task are

  1. The number of saccades during the task (n_sacc_2)
  2. The values of a and b in the equation v = b*d^a (param1_2 & param2_2)
  3. The mean number of fixations over the six images (n_fix_mean_2)
  4. The mean total time spent looking at the image (look_t_mean_2)
  5. The mean duration of one fixation (dur_fix_mean_2)
  6. The reaction to novel face over four tests (novelty_2) need more info on formula
  7. Reaction time (reaction_time_2) need more info on formula
  8. Percent time spent looking at eyes (pct_eyes_2)
  9. Percent time spent looking at mouth (pct_mouth_2)

1.2.3 Task 3: Saccades to target

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[ADD IAMGE]

The scores available for this task are

  1. Reaction time (reaction_time_3) need more info on formula
  2. Mean length of the first saccade to target (dist_3)

1.2.4 Task 4: Smooth pursuit

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[ADD IAMGE]

The scores available for this task are

  1. Reaction time (reaction_time_4) need more info on formula

2 Population description

2.1 Individuals

  • N unique individuals = 188
  • Sex:
n % val%
F 83 44.1 44.1
M 105 55.9 55.9

As a reminder in sepages: 251 boys (53%) and 218 girls (47%).

  • Birth dates:

2.2 Experiments

  • N experiments: 264

Task 2 missing for first 5 (not yet done) and when all signal was bad. (cf. notes meeting with DM 11/03/2020). Same for task 4. These tasks are more “difficult” so it’s harder to get valid signal.

2.3 Age at experiment

Older outlier:

## # A tibble: 1 x 4
##   date_birth date_exp   age_cat age_days
##   <date>     <date>       <dbl>    <dbl>
## 1 2016-12-07 2019-01-08      24     1097

True age in months = 1097 / 30.4 = 36…

Error? Exclude?

Three groups of age: 5 months, 12 months and 24 months with a majority of 24 months. Categorical age var:

n % val%
5 46 17.4 17.4
12 67 25.4 25.4
24 151 57.2 57.2

2.4 Repeated measures

Number of repeated data:

  • 118 children with 1 experiment
  • 64 children with 2 experiments
  • 6 children with 3 experiments

2.5 N with exposure

2.5.1 eye tracker 5 months

period n
exposure_T1 46/46 (100%)
exposure_T3 46/46 (100%)
exposure_M2 20/46 (43%)
exposure_Y1 14/46 (30%)

2.5.2 eye tracker 12 months

period n
exposure_T1 67/67 (100%)
exposure_T3 67/67 (100%)
exposure_M2 14/67 (21%)
exposure_Y1 13/67 (19%)

2.5.3 eye tracker 24 months

period n
exposure_T1 151/151 (100%)
exposure_T3 150/151 (99%)
exposure_M2 56/151 (37%)
exposure_Y1 40/151 (26%)

3 Eye tracker scores

First we do some univariate statistics on the scores then we look at relations between them to see if we can/need to exclude some from further analysis.

3.1 Description

Data Frame Summary

scores
Dimensions: 264 x 22
Duplicates: 0
No Variable Label Stats / Values Freqs (% of Valid) Graph Missing
1 ident [character] Unique child id 1. 22692 2. 23250 3. 24921 4. 25043 5. 25130 6. 25509 7. 16606 8. 16958 9. 17154 10. 17465 [ 178 others ]
3(1.1%)
3(1.1%)
3(1.1%)
3(1.1%)
3(1.1%)
3(1.1%)
2(0.8%)
2(0.8%)
2(0.8%)
2(0.8%)
238(90.1%)
 0 (0%)
2 S_4 [numeric] Mean (sd) : 17.6 (7.7) min < med < max: 5 < 24 < 24 IQR (CV) : 12 (0.4)
5:46(17.4%)
12:67(25.4%)
24:151(57.2%)
 0 (0%)
3 S_5 [numeric] AgeInDays Mean (sd) : 560.5 (249.6) min < med < max: 105 < 737.5 < 1097 IQR (CV) : 383.2 (0.4) 149 distinct values 0 (0%)
4 n_sacc_1 [numeric] E1SaccNum (the number of saccades) Mean (sd) : 82 (15.6) min < med < max: 38 < 81.5 < 170 IQR (CV) : 17.2 (0.2) 62 distinct values 0 (0%)
5 param1_1 [numeric] E1param1 (the value of a in v = b*d^a, with v = max displacement per sample in pixels and d = distance in pixels) Mean (sd) : 0.7 (0.1) min < med < max: 0.6 < 0.7 < 0.9 IQR (CV) : 0.1 (0.1) 262 distinct values 0 (0%)
6 param2_1 [numeric] E1param2 (the value of b in v = b*d^a) Mean (sd) : 0.7 (0.2) min < med < max: 0.2 < 0.7 < 1.4 IQR (CV) : 0.2 (0.3) 264 distinct values 0 (0%)
7 n_fix_mean_1 [numeric] E1MeanFixNum (the mean number of fixation over 5 seconds of presentation for fixation quality == 1) Mean (sd) : 9.1 (2.4) min < med < max: 2.5 < 9.3 < 14.5 IQR (CV) : 3.3 (0.3) 73 distinct values 0 (0%)
8 dur_fix_mean_1 [numeric] E1MeanFixDur (the mean duration of one fixation for fixation quality == 1) Mean (sd) : 370 (60.1) min < med < max: 272 < 358 < 697 IQR (CV) : 77 (0.2) 151 distinct values 0 (0%)
9 map_mean_1 [numeric] E1MeanMapFix (the mean of density map values at fixations points for fixation quality == 1 | 2) Mean (sd) : 0.1 (0) min < med < max: 0 < 0.1 < 0.1 IQR (CV) : 0 (0.2) 264 distinct values 0 (0%)
10 n_sacc_2 [numeric] E2SaccNum Mean (sd) : 97.8 (15.9) min < med < max: 46 < 99 < 148 IQR (CV) : 20.5 (0.2) 69 distinct values 9 (3.41%)
11 param1_2 [numeric] E2param1 Mean (sd) : 0.7 (0.1) min < med < max: 0.5 < 0.7 < 0.9 IQR (CV) : 0.1 (0.1) 254 distinct values 9 (3.41%)
12 param2_2 [numeric] E2param2 Mean (sd) : 0.8 (0.2) min < med < max: 0.3 < 0.8 < 1.6 IQR (CV) : 0.3 (0.3) 254 distinct values 9 (3.41%)
13 n_fix_mean_2 [numeric] E2MeanFixNum Mean (sd) : 8.3 (2.3) min < med < max: 2 < 8.2 < 15.8 IQR (CV) : 2.9 (0.3) 72 distinct values 9 (3.41%)
14 dur_fix_mean_2 [numeric] E2MeanFixDur Mean (sd) : 382.8 (66.8) min < med < max: 222 < 372 < 607 IQR (CV) : 80.5 (0.2) 149 distinct values 9 (3.41%)
15 map_mean_2 [numeric] E2MeanMapFix Mean (sd) : 0.1 (0) min < med < max: 0 < 0.1 < 0.1 IQR (CV) : 0 (0.2) 254 distinct values 9 (3.41%)
16 novelty_2 [numeric] E2Nov (the reaction to novel face over the four test [New-Old]./[New+Old]) Mean (sd) : 0.1 (0.2) min < med < max: -0.4 < 0.1 < 0.6 IQR (CV) : 0.2 (1.8) 255 distinct values 9 (3.41%)
17 reaction_time_2 [numeric] E2RT (reaction time at face onset) Mean (sd) : 420.2 (84.8) min < med < max: 248 < 414.3 < 844 IQR (CV) : 104.8 (0.2) 237 distinct values 9 (3.41%)
18 pct_eyes_2 [numeric] E2Eyes (percent time on eyes) Mean (sd) : 0.7 (0.2) min < med < max: 0.1 < 0.7 < 1 IQR (CV) : 0.2 (0.3) 255 distinct values 9 (3.41%)
19 pct_mouth_2 [numeric] E2Mouth (percent time on mouth) Mean (sd) : 0.1 (0.2) min < med < max: 0 < 0.1 < 0.8 IQR (CV) : 0.2 (1.1) 235 distinct values 9 (3.41%)
20 reaction_time_3 [numeric] E3RT Mean (sd) : 288.2 (58.4) min < med < max: 182 < 281.5 < 484 IQR (CV) : 69.5 (0.2) 75 distinct values 166 (62.88%)
21 dist_3 [numeric] E3Dist (mean length of the first saccade to target) Mean (sd) : 187 (28) min < med < max: 128.3 < 185.4 < 345 IQR (CV) : 28.1 (0.1) 260 distinct values 4 (1.52%)
22 reaction_time_4 [numeric] E4RT Mean (sd) : 330 (88.3) min < med < max: 96 < 313 < 750 IQR (CV) : 89 (0.3) 171 distinct values 16 (6.06%)

Also 16 missing task 4, will exclude for now.

3.2 Score vs age

  • There seems to be a strong age effect hEnce I stratify the following descriptive analyses by group age

3.3 Correlation between scores

Here we look at how the scores are correlated. We will focus on scores that are supposed to measure the same trait accross different tasks (eg reaction time at task 2 and 3) and scores that are mathematically linked (eg number of saccades and number of fixations).

3.3.1 Absolute correlations between all scores

  • all scores that measure saccade/fixations are grouped
  • the saccade equation parameters param1 and param2 highly correlated
  • the task 2 qualitative indicators pct_eyes, pct_mouth and map_mean correlated
  • correlations increase with age

David (cf notes meeting 11/03/2020)

  • param1 donne une estimation de la « vitesse de base » du sujet
  • param2 = facteur de mise a l’échelle en fonction de l’amplitude
  • pas forcément de choix évident, on va commencer avec le param1

=> drop param2_1 & param2_2

Entre n fix, n sacc et dur moyenne fix pour qual == 1 (qui sont les 3 liées) : Garder absolumùent la durée moyenne de fixation car normalement, représente l’état attentionnel de l’enfant (tps mis a traiter l’info regardée). Un comportement exploratoire va se traduire par un gd nb de fiwx, plus courtes

=> drop n_sacc_1, n_sacc_2, n_fix_mean_1 & n_fix_mean_2

Pct eyes et mouth : choisir les yeux parceque c’est la cible privilégéies de l’attention visuelle des visages statiques (pas pareil si c’est un visage parlant). Yeux utilisés sur les études du trouble du spectre autistique par ex. Indicateur a prioi plus sensible de la cignition sociale de l’enfanrt. Attention car trop peu regarder ou trop regarder les yeux peut etre le signe d’un comporteùment atypique (peut etre regarder la distance a la moyenne).

Pour la taxche 2 on va enlever le mean map car on a déjà une mesure de l’endroit de la fixation par les yeux mais qui est plus indicatrice de de la typicité du comprtement.

=> drop pct_mouth_2 & map_mean_2

Remaining scores for analysis:

  • dur_fix_mean_1
  • param1_1
  • map_mean_1
  • pct_eyes_2
  • dur_fix_mean_2
  • param1_2
  • reaction_time_2
  • novelty_2
  • dist_3
  • reaction_time_3
  • reaction_time_4

3.3.2 Correlation between tasks

Correlations on same scores/different tasks:

rowname score cor5 cor12 cor24
n_fix_mean_1 n_fix_mean_2 0.72 0.47 0.54
dur_fix_mean_1 dur_fix_mean_2 0.70 0.52 0.69
reaction_time_2 reaction_time_3 0.53 0.18 0.21
param2_1 param2_2 0.49 0.38 0.58
param1_1 param1_2 0.47 0.53 0.57
map_mean_1 map_mean_2 0.44 0.34 0.36
n_sacc_1 n_sacc_2 0.43 0.47 0.49
  • The saccades/fixation parameters rather correlated accross task
  • Map mean and reaction time not so much
  • Overall increase of correlation with age

3.4 Correlation with CBCL scores

Max correlation = 0.2

Min correlation = -0.32

Top 5 correlations:

babylab_task cbcl_task cor
n_fix_mean_2 anxscore 0.20
map_mean_1 slescorecat 0.20
n_sacc_2 anxscore 0.19
n_sacc_1 anxscore 0.19
reaction_time_2 slescore 0.18

Bottom 5 correlations:

babylab_task cbcl_task cor
reaction_time_3 anxscore -0.22
dur_fix_mean_2 anxscore -0.23
reaction_time_3 emoscore -0.24
reaction_time_3 totscore -0.24
reaction_time_3 othscore -0.32

3.5 Correlation with MCHAT/MAB scores

Top 5 correlations:

babylab_task mchat_task cor
reaction_time_2 MABwordsentprodscore_y2 0.21
n_sacc_1 MABwordsentunderstdscore_y1 0.20
n_fix_mean_1 MABwordsentunderstdscore_y1 0.20
reaction_time_2 MABwordsentlengthscore_y2 0.18
dur_fix_mean_1 MABwordsentlengthscore_y2 0.16

Bottom 5 correlations:

babylab_task mchat_task cor
novelty_2 MABwordsentlengthscore_y2 -0.16
reaction_time_3 MABwordsentprodscore_y1 -0.16
reaction_time_2 MCHATscorecat_y2 -0.17
n_sacc_2 MABwordsentprodscore_y2 -0.18
dur_fix_mean_1 MABwordsentunderstdscore_y1 -0.22

3.6 Conclusions

  • Scores are linked with age
  • Some variables are highly correlated hence the final selection of variables:
  • dur_fix_mean_1
  • param1_1
  • map_mean_1
  • pct_eyes_2
  • dur_fix_mean_2
  • param1_2
  • reaction_time_2
  • novelty_2
  • dist_3
  • reaction_time_3
  • reaction_time_4
  • These Correlations/groupings get clearer with age

A further selection is applied by excluding less interpretable vars param1_1, param1_2 and dist_3.

And indicators will be grouped as follow as they are correlated and measure the same feature:

  • Group 1: dur_fix_mean_1, dur_fix_mean_2
  • Group 2: map_mean_1, pct_eyes_2
  • Group 3: reaction_time_2, reaction_time_3, reaction_time_4
  • Group 4: novelty_2

4 Annex: Repeated measures

4.1 Correlations

Correlation for each score between each period (5 months, 12 months and 24 months):

task cor_5_12 n_1 cor_12_24 n_2 cor_5_24 n_3
dur_fix_mean_1 0.64 9 0.69 50 0.08 23
pct_mouth_2 -0.30 6 0.60 48 0.38 20
pct_eyes_2 0.50 6 0.56 48 0.08 20
dur_fix_mean_2 0.63 6 0.49 48 0.60 20
n_sacc_1 0.61 9 0.46 50 0.07 23
n_sacc_2 0.57 6 0.41 48 0.24 20
param1_1 0.10 9 0.39 50 0.33 23
n_fix_mean_2 0.74 6 0.37 48 0.33 20
map_mean_2 0.95 6 0.35 48 0.12 20
param2_1 0.08 9 0.30 50 0.18 23
map_mean_1 -0.18 9 0.27 50 0.21 23
n_fix_mean_1 0.55 9 0.26 50 0.40 23
param2_2 0.32 6 0.25 48 0.21 20
reaction_time_2 0.37 6 0.25 48 0.15 20
novelty_2 -0.03 6 0.24 48 0.11 20
param1_2 0.07 6 0.21 48 0.17 20
dist_3 0.28 8 0.14 48 0.07 21

4.2 Visualisation

4.3 Conclusions

Not sure yet what we can do with the repeated measures.